Pirkle and Wu used a model to identify the joint effects of multiple risk factors for a cluster of disorders called metabolic syndrome (MetS). These factors include increased blood pressure, high blood sugar levels, excess body fat around the waist and abnormal cholesterol levels, which collectively put a person at greater risk for heart disease, diabetes and stroke. About 34 percent of the U.S. adult population suffers from MetS.

Previous studies have examined clinical or genetic risk factors for MetS, but the UH researchers’ findings show that social and behavioral risk factors may additionally make certain groups more vulnerable to MetS than others.

“In our research, metabolic syndrome was observed in 43 percent of participants,” says Pirkle. “Not surprisingly, the risk for MetS was greater in those with low educational attainment and income, and with high numbers of childhood economic and social adversities.”

The research methods may also be applied to other diseases, such as hypertension, to identify risk clusters among other vulnerable populations in modestly sized samples. “By identifying populations most at risk for a given disease, we can better direct public health interventions to serve these populations,” explained Pirkle.